In conventional audio and speech digital signal communication systems the signal can be compressed by an encoder. A compressed bit stream can then be packetized and sent to a decoder through a communication channel frame by frame. The system comprising an encoder and decoder is also called a codec device. Speech audio compression is used to reduce the number of bits that represent the submitted speech or audio signal thereby reducing the bit rate of the transmitted signal.
Different speech coding schemes are known. For instance, a coding algorithm such as Linear Predictive Coding LPC, wave form coding or sub-band/transform coding can be employed. Depending on the specific application the algorithmic delay of the employed coding algorithm is more or less relevant. For broadcast applications a delay introduced by the codec does not have an impact and usually the introduced delay is quite high and can be in a range between 100 ms and 300 ms. In conventional conversational applications and particularly for VoIP, the delay constraint is an important factor when designing a codec. In a speech audio codec which is based on Linear Predictive Coding a linear prediction filter can be used to estimate a frequency envelope. The principle behind the use of Linear Predictive Coding is to minimize a sum of the squared differences between an input signal and an estimated signal over a predetermined time period of for example 5 ms, 10 ms, 20 ms or 40 ms etc. The coefficients of the linear prediction filter can be computed using a covariance or auto-correlation function based on a windowed version of the input signal to be encoded. Usually, the employed window takes into account part of the past samples in addition to the current samples of the input signal to be encoded. The samples which are encoded are usually centred on the employed window. Therefore, the window is applied on past samples as well as on the current encoded frame as well as on future samples which are also called look-ahead.
In some conventional Linear Predictive Coding (LPC) based encoders the LPC estimation is done after a re-sampling has been performed. For instance, in speech and audio coding algorithms targeting a wideband WB or super wideband SWB the bandwidth can be split in order to give more importance, i.e. a higher bit rate, to the low frequency part which is perceptually more relevant because the human auditory system is more sensible in the low frequency part of the signal spectrum. For example, according to G.729.1 the audio bandwidth is first split in two frequency bands of 0-4 kHz and 4-8 kHz prior to a CELP encoding (Code Excited Linear Prediction) in the first frequency band and a bandwidth extension in the second frequency band.
FIG. 1 shows a block diagram of a conventional encoding arrangement comprising an LPC estimation unit for providing LPC filter coefficients to a speech processing unit. As can be seen in FIG. 1 the received digital input audio signal can comprise frames F which are consisting of sub-frames SF. In the shown example of FIG. 1 the frame F consists of 4 sub-frames SF0, SF1, SF2, SF3 wherein the frame F can last for example 20 ms. Accordingly, each sub-frame can have the length of 5 ms comprising for example 80 samples. The received digital input audio signal S1 is applied to a re-sampling filter RSF performing a re-sampling of the input signal. The input signal S1 is received at the input signal sampling rate f1 of about e.g. 16 kHz and applied to the re-sampling filter which re-samples the received signal with a predetermined ratio of e.g. 4/5. In this way, the input signal sampling rate f1 of e.g. 16 kHz is downsampled to a sampling rate of 12.8 kHz. Accordingly, a frame F consisting of 4 sub-frames SF can comprise 4×80 samples=320 samples and is downsampled to a frame F′ having 256 samples. Accordingly, the number of samples in the downsampled frame is a power of 2 and allows to use a more efficient speech processing algorithm. The re-sampled signal provided by the re-sampling filter RSF is split and applied to the speech processing unit SPU as shown in FIG. 1 and to a LPC estimation unit which provides LPC filter coefficients for the speech processing unit SPU, or in other words is applied to both, to the speech processing unit SPU and to a LPC estimation unit as shown in FIG. 1. Accordingly, the LPC estimation is done after re-sampling. For example, the LPC filter coefficients are calculated by the LPC estimation unit by using a “Levinson-Durbin” algorithm based on the auto-correlation signal of the windowed input signal. As illustrated in FIG. 1 the window is applied also on future samples of the next frame, i.e. the LPC look-ahead.
The conventional processing arrangement as shown in FIG. 1 comprises a re-sampling filter RSF. The drawback of providing the re-sampling stage or re-sampling filter RSF is that by providing this additional filtering stage an additional delay is introduced. As can be seen in FIG. 1 the processing delay caused by the re-sampling stage or re-sampling filter is caused in the critical signal path. As illustrated in FIG. 1 the critical path in terms of delay includes a re-sampling filter delay as well as the LPC look-ahead.
The re-sampling filter RSF is for instance a linear phase FIR filter having the following transfer function:
      H    ⁡          (      w      )        =            ∑              k        =        0                    N        -        1              ⁢                  ⁢                  c        k            ·              e                              -            i                    ⁢                                          ⁢          wk                    
where C0, C1 . . . CN−1 is the coefficient sequence, the introduced filter delay is (N−1)/2. For conventional conversational applications, in particular for VoIP, this introduced delay reduces the performance of the system.
Accordingly, it is an object of the present invention to provide a method and an apparatus for providing signal processing coefficients to reduce the introduced delay of the critical signal path.